How can I perform multivariable regression with neural networks?
Have a look at sklearn's sklearn.neural_network.MLPRegressor class, which uses a multi-layer neural network to do regression. You first need to define the object MLPRegressor, for example, by specifying the value of the parameter hidden_layer_sizes, which determines the number of layers and the number of neurons per layer, then you should call the method fit on this created object and pass to it your data matrix $X \in \mathbb{R}^{n \times m}$, where $n$ is the number of samples and $m$ is the number of features.